How Transformers Work (Intuitively)

The key idea: attention

A transformer reads all tokens at once and uses self-attention to let each token "look at" the others and decide which are relevant. When processing "it" in "the trophy didn't fit in the suitcase because it was too big," attention helps the model link "it" to "trophy."

Stacked layers

Many attention layers stacked together let the model build up meaning from words → phrases → ideas. The final layer predicts the next token, one at a time.

Why it won

Unlike older sequence models, transformers process tokens in parallel, which makes them fast to train on huge datasets — the breakthrough that enabled today's LLMs.